The relative associations of aortic and carotid artery stiffness with CeVD and cognition
Bibliographic record
Abstract
We examined the relative associations of aortic and carotid artery stiffness with cerebrovascular disease (CeVD), cognition, and dementia subtypes in a memory clinic cohort of 272 participants (mean age = 75.4, SD = 6.8). We hypothesized that carotid artery stiffness would have greater effects on outcomes, given its proximate relationship to the brain. Aortic and carotid artery stiffness were assessed with applanation tonometry and carotid ultrasonography, respectively. CeVD markers included white matter hyperintensities (WMH), lacunes, cerebral microbleeds, cortical infarcts, and intracranial stenosis. Cognition was assessed by the Mini Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and a neuropsychological battery. Multivariable linear regression was conducted to determine associations of arterial stiffness with WMH and cognition, while logistic regression analysed associations with CeVD markers and dementia subtypes. Carotid artery stiffness z-score was associated with WMH, cortical infarcts, vascular cognitive impairment, and MMSE, independent of age, sex, education, vascular risk factors, and aortic stiffness z-score. Although aortic stiffness z-score was independently associated with cortical infarcts, this became non-significant after further adjusting for carotid artery stiffness z-score. We found that carotid artery stiffness had greater effects on CeVD, cognitive function and impairment in memory clinic patients compared to aortic stiffness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".